Towards a Well-being-Oriented Framework for Urban Digital Twins
Date
Authors
Patel, Urva
Ghaffarianhoseini, Amirhosein
Ghaffarian Hoseini, Ali
Burgess, Andrew
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier BV
Abstract
Urban well-being is gaining prominence as a critical pillar of sustainable development practice and urban planning; however, digital twin technology continues to focus predominantly on physical infrastructure. This paper introduces an exploratory conceptual framework for incorporating urban well-being indicators into urban digital twin platforms, utilizing New Zealand's Living Standards Framework (LSF) and adopting a policy-oriented approach to selecting well-being indicators. Through consultation with experts and a literature review, we identified six policy-relevant proxies: carbon emissions, drinking water quality, road fatalities, crime rates, work commute times, and internet access, which reflect the environmental, social, and economic dimensions of well-being. Historical data from 2017 to 2023 was operationalised in a Python-based analytical dashboard, which generates descriptive statistics, benchmarks, correlations, and Autoregressive Integrated Moving Average (ARIMA) forecasts. The study also assessed the technical feasibility of urban well-being indicators using publicly available open-source digital twin platforms such as Eclipse Ditto and FIWARE. The results indicate that integration is technically feasible; however, they are constrained by schema incompatibilities, limited native analytics capabilities, and questions of scalability regarding how proxies relate to urban well-being. As a proof-of-concept study, it explored how digital twin technology could be reshaped to support holistic, citizen-oriented objectives for well-being and complement participatory and multi-criteria approaches.Description
Keywords
44 Human Society, 33 Built Environment and Design, 3304 Urban and Regional Planning, 1205 Urban and Regional Planning, 1604 Human Geography, Urban & Regional Planning, 4406 Human geography, 4407 Policy and administration, Digital twin technology, Well-being indicators, Urban planning, Living standards framework, Real-time data integration, Predictive modelling
Source
Cities, ISSN: 0264-2751 (Print), Elsevier BV, 169, 106579-106579. doi: 10.1016/j.cities.2025.106579
Publisher's version
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© 2025 The Author(s). Published by Elsevier Ltd. Creative Commons. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.